摘要
针对强光背景下小目标图像特点,提出了一种图像增强算法。在分析了归一化不完全Beta函数取值特征后,找出了Tubbs用于拟合的α、β值在原图极亮、极暗情况下产生跳变的原因,给出了其服从连续变化规律的解释,并在采取模拟退火算法求取其最佳值时,给出了相应处理办法,从而确定了最佳变换曲线,实现原图像的自适应增强;然后采取基于三帧累加图像流处理的办法来累积小目标能量及平滑噪声。仿真实验结果表明,该方法能有效实现强光背景下小目标图像的增强。
An algorithm for image enhancement of small target in strong light level background is proposed in this paper. After analyzing the characters of choosing parameters for incomplete Beta＇s function, the reasons of the jumpiness for α and β＇ s value which Tubbs use to estimate the transformation in the condition of the exceedingly bright or dark original image are founded. It is explained that their changes are continuous. Then, the processing way for solving their best value by simulated annealing algorithm is given. So the optimum corresponding transformation curve is obtained, and the aim of the original picture＇s self-adaptive enhancement is achieved. Furthermore, by using the way of images stream based on adding three continuous frames, the small target energy is enhanced and the noise energy is smoothed down .The experimental results show that the method can enhance effectively small target images in strong light level background.
出处
《光电工程》
EI
CAS
CSCD
北大核心
2007年第12期87-91,123,共6页
Opto-Electronic Engineering
基金
国防预研基金资助项目
关键词
强光背景
低对比度图像
图像增强
BETA函数
模拟退火算法
strong light level background
low contrast image
image enhancement
Beta function
simulated annealing algorithm
